Mortgage and education financial optimization

ABSTRACT

The invention relates to systems and methods for optimizing investments in view of anticipated education or mortgage expenses. One an allocation of assets among investments is determined, and education or mortgage costs are to be considered, systems and methods of the invention assist in optimizing a tax treatment by allocating the chosen investments from accounts based on the tax treatment of those accounts. The invention includes a computer system and methods of the invention run on a computer system.

CROSS-REFERENCE TO RELATED APPLICATIONS

This patent application is a continuation of application Ser. No.12/564,574, filed on Sep. 22, 2009, which is a continuation ofapplication Ser. No. 11/928,945, filed on Oct. 30, 2007, which is acontinuation of application Ser. No. 09/825,426, filed on Apr. 3, 2001,which claims priority from Provisional Application 60/194,158, filed onApr. 30, 2000, and is a continuation-in-part of application Ser. No.09/346,602, filed Jul. 2, 1999 and claims benefit of U.S. ProvisionalApplication Ser. No. 60/113,859, filed on Dec. 24, 1998, the entirecontents of each of these applications being hereby incorporated byreference herein.

FIELD OF THE INVENTION

The present invention is directed towards financial analysis, and moreparticularly towards investment location optimization software.

BACKGROUND

Recent changes in the tax code and the ability of individuals to managethe investment of their retirement accounts have created manyopportunities for maximizing growth over time, but have also introduceda new level of complexity into individual investment decision.Determining the best investments and strategy is a daunting task. Afundamental problem faced by all investors and financial advisors iswhich account—retirement or taxable—to put each investment in with theirgiven asset allocation. Two factors strongly influence these decisions.First is the asset classes, such as stocks and bonds (and their subcategories) each which has various advantages and disadvantages,including expected return and risk. Second is the tax status of both theinvestor and the investment, which typically breaks down into taxableinvestment accounts and tax deferred investment accounts (e.g., 401Ksand IRAs). A decision must be made about how to distribute the assetclasses between the taxable accounts and tax deferred retirementaccounts. For example, if a split of 60% stock (or stock funds) and 40%bonds (or bond funds) make sense for an investor (it's an appropriateasset allocation), and this investor has $75,000 in an IRA and $25,000in a taxable brokerage account, the question is investor has $75,000 inan IRA and $25,000 in a taxable brokerage account, the question is“where should the $60,000 stock and the $40,000 bond allocations belocated for maximum long-term benefits?” Should he hold the stocksentirely in the retirement account or hold $25,000 in the taxableaccount and $35,000 in the IRA? The present investment addresses andoptimizes this question.

Because of the different income and growth characteristics ofinvestments in the various asset classes and the different ways andrates at which they are taxed, and by whom (Federal, state, local) thedecision about which account to put each asset class (investment) has avery significant impact on the after-tax investment accumulation overtime. Financial advisors have been forced to “optimize” as best theycould by applying their knowledge of each investments' characteristicsand knowledge of the tax laws to approximate what they thought would bethe highest after tax accumulation for the target investment horizon.The process is very much a “seat of the pants” exercise and the outcomedepends on the advisor's level of knowledge and their ability tomentally integrate and process a set of highly complex variables.

As with any uncertain process, advisors and experts disagree upon thebest strategy for investment. An article by Venessa O'Connell in theWall Street Journal (Capital-Gains Tax Cuts Mean It's Time To ReviewYour Tax-Deferred Strategy, WSJ Aug. 29, 1997 page C1) stated that thequestion of whether to keep stocks or bonds in tax-deferred accounts hasbeen debated among the wealthy for years. The article further went on toquote Harold Evensky, a highly respected financial advisor at Evensky,Brown & Katz in Fla., who recommended that high-income investors keepstocks in taxable accounts and favor corporate bonds in tax-deferredaccounts. However, this general advice may not prove optimal, as will beshown below.

While experts disagree on even the basic strategies, the typicalinvestor often doesn't even address the issue. Financial advisors oftenspend too little time on the issue of investment location, therebyending up with less than optimal investment strategies. More often thannot individual investors are oblivious of the issue to their financialdetriment.

Several tools and systems attempt to address this problem. Spreadsheetscan be constructed to “run the numbers”, but the outcome depends on theinput into the system. By changing input assumptions it is possible totest different scenarios to see which combination gave the best result.While this is an improvement over the “seat of the pants” method, it isnot a true optimizer.

Similarly, commercial calculators may become available Which obviate theneed to construct spread sheets, but perform essentially the samefunction as the spreadsheets. The commercial calculators calculateaccumulation amounts over time based on a set of assumptions. Bychanging the assumptions, the user is able to test different sets ofassumptions (strategies). This is an incredibly time consuming andburdensome task given the number of variables and the possible number ofcombinations. A large number of variables must be considered with a hugesearch space. For example, 80 variables will result in over 14 billionpossible combinations. None of the above approaches will yield anoptimum solution.

There are several other approaches for developing an optimizationsolution for this complex problem with varying degrees of success. Abrute force approach is simply to try every possible combination andcalculate the best result. This can work fine, but with real worldproblems, the number of combinations is so large that this approach isnot practical given a reasonable time scale.

Numerical calculator optimization techniques have been used to attemptto solve optimization problems and are now available in most advancedspreadsheet programs. But these techniques have limitations. Forexample, they lend themselves to optimizing independent numeric inputsfrom which a desired output is calculated. They are less capable ofoptimizing problems involving sequencing or scheduling. Also, they are“exploitation” and not “exploration” techniques. This means that given areasonable starting solution (a set of input values), the numericoptimization will converge to a near optimal solution. However, they arenot capable of exploring areas of space where good solutions exist. Thisis because numerical optimization techniques can often get trapped inlocal optimal solutions. Another limitation of numerical optimizationtechniques is that they are not suitable if the outcome cannot beexplicitly calculated. For example, When the outcome is a subjectiveassessment by an expert or an observed performance.

Another approach is the use linear program techniques. These can workwell when optimizing the numeric parameters of a recipe type problem.However, with the particular type of optimization problem related toinvestment account selection, it becomes very difficult to represent theproblem in terms of linear numeric parameters. Also, as the number ofparameters and equations increase, the calculations and solution surfacebecome extremely complex.

Further, false optimum solutions are prevalent, with no clear indicationof recognizing the false solutions.

None of these approaches help to find an optimal solution in areasonable amount of time (both real time and computer time).

SUMMARY

The present invention comprises an investment location optimizer. Oncean investor or investment advisor determines the appropriate assetallocation (investment mix) and that there are both taxable accounts andtax-deferred investment accounts, the invention will optimize/maximizethe investor's ending after-tax asset accumulation, which is theobjective of all investors. This is accomplished by allocating thechosen investment vehicles between the taxable and tax-deferred accountsin an optimum way.

The present invention includes a system for determining an investmentstrategy for an entity with assets in taxable and tax-free accounts. Itincludes an account information input component, to accept informationregarding the assets in the taxable and tax-free accounts for theentity; an investment selection input component, to accept informationregarding, a plurality of investments, including an indication of apercentage amount to invest in each of the plurality of investments; anaccount amount selection component, to select an amount to invest fromthe taxable accounts and tax-free accounts in the plurality ofinvestments which substantially matches the indication of a percentageamount to invest in each of the plurality of investments; and a timehorizon input component, to accept an indication of a time horizon. Areturn on investment calculation component, then calculates a return oninvestment for the entity based on the information regarding the assets,the information regarding a plurality of investments, the indication ofa percentage amount, the selected amount to invest from the taxable andthe tax-free accounts, and the indication of a time horizon. The accountamount selection component selects an amount from the taxable andtax-free accounts in order to produce a maximal return on investment forthe entity at the time horizon.

In one embodiment, the account amount selection component randomlyselects amounts from the taxable and tax-free accounts, and the returninvestment calculation component calculates a return for the entitybased on the randomly selected amounts. The steps of randomly selectingamounts from the taxable and tax-free accounts and calculating a returnare performed a plurality of times, and the system outputs selectedamounts from the taxable and tax-free accounts which produce a maximalreturn.

In another embodiment, the account amount selection component selects anamount from the taxable and tax-free accounts using Genetic Algorithms(GA) in order to produce a maximal return on investment for the entityat the time horizon. This embodiment includes a chromosome structure,for use with the Genetic Algorithms, wherein the chromosome structureincludes a plurality of values, each value being an indication of anamount from the tax-free accounts to invest in a selected one of theplurality of investments.

Advantages of the present invention include optimization of investmentoutcome when there are two basic kinds of investor accounts: 1) taxableaccounts and 2) tax-free accounts such as Roth accounts. In additionthere are other kinds of investor accounts with their own unique taxcharacteristics that can be incorporated into the present invention.This would provide a broader and far more complex selectionoptimization.

The present invention rose from the need to help make optimal decisionsfor clients and investors. The total asset accumulation in an investor'sportfolio over time will vary dramatically depending on the decision ofwhich account to invest in which asset class. Through the use of thepresent invention, the inventors are able to increase the terminalportfolio value typically between 5 and 40% with no increase in risk tothe investor. The risk lies with the asset allocation and specificinvestments selection not where they are located. All relevant variableshave been incorporated into the present invention in order to trulyoptimize the end period accumulations.

The illustrative embodiment of the present invention comprises a hybridGA-Heuristic search strategy. The hybrid approach is reflected both inthe implementation of the GAs and the methodology of applying it tosolve problems.

In broad terms, the following are the five steps to determine theoptimum investment portfolio for each client, as outlined in FIG. 1.Fact gathering 20 includes setting goals, identifying risk tolerance,making retirement projections, agreeing on the appropriate time horizonsand identifying the available investments. The next step is AssetAllocation 22. Studies show that 50 to 90% of total pre-tax returns aredetermined by asset allocation. Given the results of the fact findingphase 20, determining the appropriate mix between stocks (domestic,international, small cap, large cap), bonds (short-term, long-term,domestic, international, tax exempt), and cash which makes the mostsense for them is among the most important decisions in the investmentprocess.

In the step of Investment Selection 24, investors choose among theavailable investment options in each asset category to fund the assetallocation chosen in Step 22. The investor will select from theavailable mutual funds or individual stock, bonds and money marketinstruments. Then there is Account Selection 26, which includesdetermining which accounts (retirement/tax free, non-retirement/taxable,children, trusts, etc.) are best suited for the investments and assetallocation determined in Steps 22 and 24. These accounts are all taxeddifferently. Accordingly, this decision is primarily tax motivated withthe objective of maximizing the after-tax accumulations over time.

Finally there is Monitoring 28. After implementation the ongoingmonitoring of the portfolio is essential as circumstances change.

With regard to Step 26 Account Selection, there is no standard system orformula for allocation. It is here that investors and financial advisorsneed to make the complex decisions about in which account to place whichinvestment. There are a great number of variables which impact theaccount selection decision. They include the time horizon, current andfuture tax brackets (both state and federal), current and future capitalgains rates, relative spread between bonds (municipals, federal,corporate), portfolio turnover, investment yields and appreciationrates, and relative proportion of overall portfolio in account types(retirement, non-retirement, children, trusts).

The illustrative embodiment of the present invention simultaneouslytakes into account the following variables: Federal taxes includingincome taxes (8 brackets) and capital gains taxes (3 brackets); Statestaxes including income and capital gains taxes (different in all 50states and many have multiple brackets); Investment characteristics ofnumerous asset classes which are defined in terms of incomecharacteristics (including taxable, tax-exempt, growth characteristicsand turnover); time horizon (in years); before and after liquidationvalues; proportion of assets in taxable and tax-free accounts; andrelevant investment mix.

Advantages of the present invention include a marked level ofimprovement in outcome from the application of the present invention.Typically the improvement is in the 5-40% range over 20 years. This issignificant, and remember, it is a complete freebie. This is, the endresult of the investment process is improved significantly, with noincrease in risk as it is the same investments just in better locationsfrom a tax stand point. And, as previously discussed, the means ofachieving an optimum solution is not available by any other means.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other features and advantages of the present inventionwill be more fully understood from the following detailed description ofillustrative embodiments, taken in conjunction with the accompanyingdrawings in which:

FIG. 1 is an outline of steps in an investment process;

FIG. 2 is a block flow diagram generally showing information inflow andoutflow to a system according to the present invention;

FIG. 3 is a block diagram showing a more detailed flow of information ascompared to FIG. 2;

FIG. 4 is a block diagram showing an investment optimizing componentaccording to one embodiment of the present invention;

FIG. 5 is a block diagram of a computer system according to oneembodiment of the present invention;

FIG. 6 is a user interface input screen for entering entity dataaccording to an illustrative embodiment of the present invention;

FIG. 7 is a user interface input screen for entering investment dataaccording to an illustrative embodiment of the present invention; and

FIG. 8 is a user interface output screen for displaying resultsaccording to an illustrative embodiment of the present invention.

DETAILED DESCRIPTION

FIG. 1 outlines steps used in planning an investment strategy for anentity, such as a person. Fact gathering 20 includes setting goals,identifying risk tolerance, making retirement projections, agreeing onthe appropriate time horizons and identifying the available investments.The next step is Asset Allocation 22. Studies show that 50 to 90% oftotal pre-tax returns are determined by asset allocation. Given theresults of the fact finding phase 20, determining the appropriate mixbetween stocks (domestic, international, small cap, large cap), bonds(short-term, long-term, domestic, international, tax exempt), and cashwhich makes the most sense for them is among the most importantdecisions in the investment process.

In the step of Investment Selection 24, investors choose among theavailable investment options in each asset category to fund the assetallocation chosen in Step 22. The investor will select from theavailable mutual funds or individual stock, bonds and money marketinstruments. Then there is Account Selection 26, which includesdetermining which accounts (retirement/tax deferred,non-retirement/taxable, children, trusts, etc.) are best suited for theinvestments and asset allocation determined in Steps 22 and 24. Thisdecision is primarily tax motivated with the objective of maximizing theafter tax accumulations over time.

Finally there is Monitoring 28. After implementation the ongoingmonitoring of the portfolio is valuable as circumstances change.

Focusing on Step 26 Account Selection, there is no standard system orformula for allocating investment funds from taxable and tax-deferredaccounts. It is here that investors and financial advisors need to makethe complex decisions about in which account to place which investment.There are a great number of variables which impact the account selectiondecision. They include the time horizon, current and future tax brackets(both state and federal), current and future capital gains rates,relative spread between bonds (municipals, federal, corporate),portfolio turnover, investment yields and appreciation rates, andrelative proportion of overall portfolio in account types (retirement,non-retirement, children, trusts).

FIG. 2 illustrates an asset allocation optimizer 36 according to thepresent invention. An illustrative embodiment of the present inventionstarts with a predetermined Asset Allocation 30. This includes taxableassets and accounts 32 and tax deferred assets and accounts 34.Typically, these asset allocations 30 are pre-divided into variouscategories. For example, an entity (such as a person or business entity)may have funds in a taxable account, where taxes are due each year; anda tax-deferred, where taxes on the principal and/or interest are not dueuntil the funds are withdrawn, or the individual reaches a certain age.The types of accounts for which the present invention is applicableinclude Taxable, IRA, 401K, Keough, Roth IRAs; trust accounts;foundations; corporate charitable trust accounts; children's accounts.

While these funds are in different accounts 32 and 34, they may beinvested in different investments. A feature of the present invention isdetermining which accounts to use for each investment that results in amaximum after-tax accumulation.

These predetermined asset allocations 30 are provided as inputinformation into an investment location Optimizer 36. Other informationinput to the investment location Optimizer 36 includes investmentcharacteristics 38. As detailed in FIG. 3, investment characteristics 38include details about the various selected or potential investments,including ordinary income, yield, percent tax, long term capital gaindistributions, unrealized appreciation, and investment turnover. Thisinvestment characteristic information 38 is specific to each investment.Such information may be stored in a separate database, or enteredspecifically for a specific entity.

Other information entered into the investment location Optimizer 36includes tax rates and time horizon information 40 which generally ispeculiar to the individual entity. Such individual information 40includes the federal income tax rate, state income tax rate, capitalgains tax, tax deferred investments (accounts) and total investments forthe individual. Other information includes the time horizon which is theperiod of which to determine the maximal growth. The investment locationOptimizer 36, FIG. 2, then determines an optimized solution which is anoutput 42 in the form of an optimized accumulation 44. This informationis similar to the original investment location information 30, exceptthat now the amount of taxable investment accounts 46 and tax deferredinvestment accounts 48 are selected to produce an optimal result at theend of the time horizon. Other information, including the projectedinvestment value at the time horizon, and percentage improvement, may beoutput, as will be discussed below.

The investment location optimizer 36, FIG. 4, includes two majorcomponents in the illustrative embodiment of the present invention. Anaccount amount selection component 50 receives as input thepredetermined investment location 30 and works to adjust the properinvestment location to produce an optimal solution. Another component isthe return on investment calculating component 52. This return oninvestment calculating component 52 performs calculations to determinethe value of the various investment over the time horizon. Thereforethis return on investment calculating component 52 accepts input of theinvestment characteristics 38 as well as information from the accountamount selection component 50 as shown by arrow 54. The return on theinvestment calculating component 52 performs standard calculations fordetermining growth based on interest, turnover, mean variance analysis,and other features of an investment, including the tax characteristics.The information returned by the return on investment calculatingcomponent 52 is provided as feedback 56 to the account amount selectioncomponent 50, thereby allowing it to receive feedback on variousoptimizations and determine an optimal solution.

The output 42 from the account amount selection component 50 is in theform of the optimized investment locations which are returned to theuser of the system.

A computer system for running an embodiment the present invention isshown in FIG. 5. A user may interact with the system using a workstationor other display, to input information and run the system. A computersystem including a user interface application interacts with the user,and stores information regarding accounts and assets in a database. Theoptimization system interacts with the database to retrieve and storeinformation. The optimization system also may interact directly to theuser, either directly or through the user interface application orsystem.

One embodiment of the asset allocation optimizer 36 uses Monte Carlosimulation to determine an optimized allocation. The account amountselection component 50 generates ranges of percentages of taxable vs.tax-deferred accounts to invest in particular investments. Then thesystem randomly selects percentages within those ranges, whereupon thereturn on investment calculating component 52 determines the resultsbased on the randomly selected percentages. This cycle is repeated manytimes, with the system remembering the best result. The selection ofrandom percentages can be adjusted depending upon the selection process,for example random selections within the range can be uniform(pseudo-random), or skewed, such as logarithmic over the range, or overa normal distribution curve.

An advantage of the Monte Carlo technique is that it can also be appliedto variable yields for various investments. For example, an investmentstock may have a projected yield, but more likely it will vary overtime. The present invention allows investment yield (and otherparameters) to be entered as a range, instead of as a specific return.This range can be defined so that random values selected within therange are even distribution, bell curve, stepped, skewed, etc. By usingMonte Carlo techniques to factor in volatility of one or moreinvestments and generate realistic samples of the results, a betteroptimized allocation is produced. Further, results can include a “bestcase” and “worst case” result, which allows for more prudent allocationdecisions.

The Monte Carlo technique may be used alone, or in combination withother optimization techniques, including the GA (Genetic Algorithm)embodiment described below. For example, the Monte Carlo technique isuseful for selecting randomly distributed samples used to “seed” thegene pool for GA fitness and cross-breeding evaluations. In other words,to improve the account selection starting point of the presentinvention.

The illustrative embodiment the present invention uses GeneticAlgorithms (GA) to help select an optimized investment allocation. GAsare techniques for solving optimization problems inspired by the theoryof evolution and biogenetics. These algorithms are useful for exploringlarge search spaces for optimal or near optimal solutions. The basics ofa genetic algorithm are:

1. Representing possible solutions to problems as a string of parameters(numbers). This string is called a chromosome and the parameters withinit are called genes; 2. Randomly creating a number (generation) of thesechromosomes; 3. Calculating the effectiveness of each chromosome as asolution to the problem then ranking the chromosomes in order ofeffectiveness (fitness to survive); 4. Creating a new generation ofchromosomes by randomly selecting pairs of chromosomes (parents) andmixing their genes to form child chromosomes (This process is called‘crossover’ and the selection of the parents is biased to more effective(fit) parents. Another variation called ‘mutation’ involves randomlychanging one or more genes within a chromosome. Mutation helps GAsystems to avoid false solutions and too-narrow convergence on one areaof the search space); and 5. Repeating steps 3 to 4 for a number ofcycles (generations).

The randomness of the above process allows the effective exploration ofthe space of solutions. While the selection of effective solutions(chromosomes) and the mixing of their genes allows the accumulation ofgood features from partially good solutions. As a result, geneticalgorithms can explore large domains and converge on good solutionsrelatively quickly. GA's also give a powerful trade off between the timetaken to reach a solution and the quality of the solution.

The two basic steps in developing solutions using GA's are anappropriate representation of the problem and a method of assessing theeffectiveness (cost) of a solution. The easiest representation of aproblem for GA implementation is as a string of numbers. Each number isrepresented by a gene that can be constrained by the minimum and maximumvalues it can take. A cost function is defined which derives a value forthe cost of the solution from a given set of gene values. In such arepresentation, each gene represents a different numeric parameter ofthe solution. Alternatively, a chromosome can be used to represent asequence of jobs which requires optimization. In such a case the numberof genes will equal the number of jobs to be sequenced and the value ofeach gene will be unique and range from 1 to the number of tasks.

The genetic structure used in the illustrative embodiments a singlenon-sequence chromosome, named TaxDeferred with a variable number ofgenes, ACTD (Asset Class Tax Deferred). Each asset class is representedas a gene containing the dollar value in tax deferred accounts on thischromosome. That is, the GA component generates values for the amount intax deferred accounts for all asset classes, and the cost functionwritten for this application computes both the amount in taxableaccounts and the total value for that allocation to taxable and taxdeferred accounts. There is applied a sum constraint which requires thatthe total tax deferred dollars in all genes must add up to the total taxdeferred dollars specified by the user. The fitness is the measure ofthe value at the time horizon.

As previously mentioned, in the illustrative embodiment the initialchromosome is initialized to a set of values that represent the currentvalue in tax deferred accounts in order to provide a reasonable startingpoint for the optimization. By utilizing current values, theillustrative embodiment converges to an optimal solution within onegeneration (initial chromosome “pool” created by mutation, and ageneration “pool” including crossover). Experiments using two and sevengenerations showed some improvement over using one generation, with atradeoff in increased time for computation. Multiple generations may beused for incremental improvements to an optimal solution, or if thecurrent values are not already “optimized” in that the accounts wereselected by a naive investor. Therefore the present invention works bothfor experienced investors and, advisors as well as naive users and maybe adjusted accordingly for specific investor types.

The illustrative embodiment of the present invention is implementedusing Microsoft Access 97 and XPERTRULE KBS by Attar Software. However,any database could be used for this purpose as could any heuristicproblem solving algorithm. The illustrative embodiment runs on a generalpurpose computer such as an Intel based processor running a standardoperating system such as Microsoft Windows or Linux. However, thepresent invention can run on any type of computer system, mainframes topalm computers, or on calculators such as financial calculators.Further, the present invention may be available locally or remotely tousers over a network based system such as the internet or modernconnections. For example, users can access a web site (either generallyor with a personal account number), enter information and run theoptimizing system. Users can also store their personal information insecure accounts at the web site.

A full description of the specific GA system used to implement theillustrative embodiment can be found the XPERTRULE Reference ManualRelease 3.63, as provided by Attar Software Limited, and is fullyincorporated herein by reference. Software applications fall into twocategories; analysis and synthesis. Analysis applications arerepresented by the traditional input/output model of data processingwhereby input data is processed procedurally or heuristically togenerate the output data. Synthesis applications involve the reverseprocess of deriving the input data required to generate certain desiredoutputs. This is a difficult task since there are, in most cases, noformulae or rules to derive inputs from outputs. This is furthercomplicated by constraints imposed on the acceptable values of inputdata. Optimization is the process of deriving, values of input data thatsatisfy constraints and which results in the desired output data.

The GA component of the illustrative embodiment first computes theportfolio value Oven the current location of assets between taxable andtax deferred accounts, and stores this for comparison to the final valuedetermined to be best by the cost function.

The GA component then initializes the GA to a set of values thatrepresent the current value in tax deferred accounts in order to providea reasonable starting point for the optimization. This is not necessaryto reach an optimal value, but it seems to speed up the processconsiderably. In the illustrative embodiment, a first iteration (orpool) of chromosomes is performed for fifty iterations. The iterationsdiffer through random changes (mutations) in the chromosome. Ageneration is then created, using random crossovers with another set of50 iterations. This cycle may be repeated as desired.

Now, given a particular set of values of tax deferred dollars in eachasset class, the value function determines the total value of theportfolio. If this value is better than previous values, then it isretained as the best solution so far, otherwise, it is discarded.

Computations used by the value function in the illustrative embodimentto reach its conclusions are listed in Appendix A of U.S. Pat. No.6,240,399, including valuation functions to compute the future value ofvarious investments including stocks and bonds. For the illustrativeembodiment, the GA component writes its conclusion to a file. U.S. Pat.No. 6,240,399 is herein incorporated by reference in its entirety.

FIG. 6 illustrates a user interface front end for use with anillustrative embodiment of the present invention. As shown in the inputwindow 64, information including an account identification, and abusiness or individual indication are entered along with the first andlast name and age of the entity. This information may be saved in adatabase to allow future recall and changes. Other information which maybe used in calculations or simply for data base entry are also entered.Allocation data including the total assets available and the totalassets in a tax deferred account are input along with the (combined orseparate) federal and state tax rate for the individual. An optimizationmethod may be entered including after liquidation are also entered.Finally, the time horizon in years is also entered on this screen 64.

Clicking on the button marked ‘Asset Class’ brings up the following form66 as shown in FIG. 7, on which the Clients' various assets are enteredalong with the current Taxable/Tax Deferred allocation. There arepossibly many user-defined asset classes which generally fall into oneof two types: Stock or Bond. For each asset class, the user may enter orselect the following data: percent taxed by federal and stategovernments; ordinary income (dividend) percent; yield percent forbonds; long term capital growth distribution; anticipated unrealizedappreciation; percent and amount to be allocated to each asset class;percent and amount currently allocated to taxable and tax deferredaccounts; average turnover time; and capital gains tax rate.

Also entered at this stage is a preliminary allocation between thevarious investments which is shown by label 68. Here, there is a percentallocation between the various investments which will equalapproximately 100%. The illustrative embodiment will also calculate theinvestment amount based on the total assets available based on thepercentage as shown by label 70. Alternatively, the amount entered maybe entered in monetary units wherein the percentage will be calculatedautomatically. Finally a current allocation between taxable and taxdeferred accounts is entered 72. This provides a starting point for theoptimization process and further will provide an ability to view howmuch the optimization has provided for.

When the user clicks the “Optimize” button on the user input or editscreen 64 FIG. 6, the appropriate data is sent to the optimizing system.In the illustrative embodiment, data is written to an ASCII text file bythe database, and are subsequently read by the optimizing system. Insubsequent versions, OLE 2 or other protocols may be used for datacommunication. Prior to optimization, some calculations are done toprepare the data for optimization. This code, written using XPERTRULEKBS, is shown in Appendix A of U.S. Pat. No. 6,240,399, the contents ofwhich is incorporated by reference herein in its entirety.

FIG. 8 shows the result screen 74 which presents the output from theoptimization process. As shown by label 76 for the present example, theinvestment allocation optimization system was able to provide an 11%improvement over the current strategy with a time horizon extending outto March of 2039. As output by the system, the data as shown by label 78is a new allocation between the taxable account and tax deferred accountwhich provides more value at the time horizon. In performing thesecalculations, the optimization system maintains the limits as providedby the account data, for example if an entity wants to invest 25% in aparticular investment, then there is not enough assets available in atax deferred account to fully fund 25% then assets will be distributedfrom the taxable account to make up the difference. An improvement uponthis strategy, is to provide suggestions to the entity to provide morefunds available in their tax deferred account should that person's taxsituation allow for such a move.

The illustrative embodiment of the present invention was tested withdata to check the hypothesis of Evensky, as discussed in the previouslycited Wall Street Journal article. Evensky recommended keeping stocks intaxable accounts and bonds in tax-deferred accounts. A scenario was runusing data of $200,000 total assets, with $100,000 in tax-deferredaccounts. The federal tax rate was 42% and state tax rate 6%, with ahorizon of forty years. Two investments were entered, a bond investmentreturning 6%, and a stock investment returning 13%. The scenario wasstarted with all the tax-deferred assets (50%) in the bond investment,and all the taxable assets (50%) in the stock investment, therebyfollowing Evensky's advice. The results from running the system was verydifferent. The illustrative embodiment instead computed that putting allthe taxable assets in the bond investment, and all the tax-deferredassets in the stock investment would results in a growth in value to$7,281,432, which was a 94% improvement over the initial allocation.Therefore, for the example tested here, Evensky's hypothesis is clearlynot the best investment strategy.

The present invention includes additions and enhancements which providemore utility for investors and analysts. These additions includedifferent optimization techniques and algorithms, including rule-basedexpert systems, neural net processing to recognize patterns and learnoptimization techniques, fuzzy logic, linear programming, exhaustivesearch, and various combinations thereof.

Further, different types of accounts may easily be added to the presentinvention, including Roth IRA, annuities, various trusts, 401k,custodial accounts, 529 investment plans, corporate accounts, etc.Specific investment or class of investments characteristics may beadded, for example the system can optimize the type of bond, i.e., ifbonds are best suited for retirement account, then use 6% yieldingcorporate bonds, if best suited for taxable account and tax bracket atleast 28%, use 4% municipal bonds.

Details for other types of accounts include:

ROTH IRA—investments accumulate within a ROTH (popular retirementaccount) tax-free and assuming certain rules are met (i.e. nowithdrawals allowed prior to age 59.5 without penalty) distributionscome out tax-free. Furthermore unlike most other retirement accounts,there is no required distribution beginning date of age 70.5. As aresult the system can determine whether makes sense to put an investor'shighest total returning investment in a ROTH to enjoy maximum long-termaccumulation. ANNUITIES—investments within an annuity accumulate on atax-deferred basis like most retirement accounts. The major differencesare the required distributions begin later (age 85 or 90 versus 70.5)and only the earnings are taxed as ordinary income as opposed to theentire distribution being taxable with normal retirement accounts. Anannuitant recovers tax-free the portion of his payouts that representhis original purchase price on the annuity. System inputs for this typeof account include the cost of the annuity and the anticipated beginningpayout date. For example an investor may have purchased an annuity for$10,000 (input) and its value is currently $14,000 (input) with ananticipated beginning payout date in 7 years (input). Depending uponwhich investment is optimally located in the annuity it will haveaccumulated to a certain amount by the time of the first distribution.If thr example the value of the annuity at that time were $50,000 thenroughly 80% ($40,000 earnings as a % of value) would be taxable.

Note that there is a limit as to which investments are available withinany particular annuity. Individual stocks can not be purchased by law inan annuity. Each annuity product has mutual fund-like sub accounts. Somehave a large number to pick from and others a very limited number.Accordingly as another input for all investments is a block put on anyinvestment not available within any annuity the investor has. The systemwould not consider that investment as being available for that annuityin the optimization process.

NON-DEDUCTIBLE IRAs & OTHER POST-TAX RETIREMENT ACCOUNTS—are taxed inroughly the same way as annuities except they are required to begindistributions at age 70.5 (versus 85 for annuities). An additional inputwould then be the investor's non deductible contribution in this type ofaccount. Distributions at 70.5 (per preprogrammed IRS tables) have atax-free return of principal component to them. TRUSTS—an investor mayconsider investments within a trust part of the overall familyportfolio. Trusts may be taxed differently than other taxable accountsin an overall portfolio. For example, the top marginal federal tax rateof 39.6% is reached at roughly $280,000 for individuals with the first$30,000 only being taxed at 15%. For most trusts, 39.6% is reached atroughly $10,000 (capital gains taxes may be the same rate for either(currently 20%)). Accordingly a trust might be in a much higher taxbracket than an individual for ordinary income items and a high ordinaryincome investment like a corporate bond may be better located in anindividual's account rather than a trust. Accordingly, an additionalinput for each trust is how it is taxed.

Note that appreciation of securities in trusts may never be taxed undercertain circumstance. For example a charity may get the assets at somefuture date. An additional input would shut down the related capitalgains tax on investments within that trust.

CHILDREN'S ACCOUNTS—an investor may consider investments taxable to achild as part of the overall family portfolio. Accordingly, the taxrates applicable to other family members accounts is an additionalinput. A child may be subject to a different tax rate for both ordinarytaxes as well as capital gains taxes. EDUCATIONAL ACCOUNTS—may be taxeddifferently depending upon which IRS allowed plan an investor uses. Someplans are tax deferred until distributions are made and then taxedentirely at the recipient's ordinary tax rates. CORPORATEACCOUNTS—investments are sometimes located inside controlledcorporations and are then subject to corporate tax rates.

Other features are easily integrated, for example a foreign tax creditfeature may be added, wherein the foreign tax credit can only be takenin taxable accounts as an additional input.

Foreign countries often assess taxes on investment income of UScitizens. To mitigate the inequity of double taxation the federalgovernment allows a credit on an individual's tax return for foreigntaxes paid in a taxable account. There is no such credit given inretirement accounts. Accordingly, an input to help determine the optimallocation of investments is the dollar amount of the expected credit forall foreign investments. Alternatively the input is expressed as a % ofthe value of the investment. The system then factors in the tax savingsof the credit if held in a taxable account. This would obviously impactthe long-term accumulations that the system is optimizing. Whether it isworthwhile to forego the credit and hold the investment in a retirementaccount would be a function of the many other variables input.

Another embodiment of the present invention is for initial optimizationfor the type of bond. One embodiment of the present invention takesgiven investments and searches for the best account locations tomaximize long-term accumulations. However, the investments might change.An investor may have a corporate bond that pays 6% per year in interest.If it were held in a taxable account the interest would be taxed at theinvestor's marginal rate of tax. In a retirement account it would betaxed along with all other components (contributions, capital gainsetc.) of the account with the marginal rate of tax applied to the amountwithdrawn, possibly in many years at the investor's then marginal rateof tax. A tax-free municipal bond may be the effective equivalent to atop-rated corporate bond in terms of risk etc. with the only substantivedifference being interest yield. Because of the tax-free nature ofmunicipal bonds, municipalities are always able to pay less in interestthan their taxable bond counterparts. Accordingly, if a bond is to beheld in a taxable account, investors will calculate whether a tax-freemunicipal bond would yield more than a taxable corporate bond wouldafter the taxes are paid. Typically investors in the highest taxbrackets will use municipal bonds for their taxable accounts (no oneever holds municipals in their retirement accounts, as they are nottax-free there). Therefore, even though x amount in bonds may be a givenfor an investor, the type of bond chosen (taxable or tax-free) wouldnormally be a function of its location (taxable account or retirementaccount) and the investors tax bracket.

If for example, an investor has committed to investing $10,000 in bondsand if held in a retirement account then a corporate bond will bepurchased which will yield 6%, if the bonds are held in a taxableaccount then based on the investors tax bracket of 36% they willpurchase a municipal bond paying 4% as 4% is greater than 3.84% which isthe after-tax yield on a corporate bond for this investor (6%×(1-36%):If the investor's tax bracket was 15% then the corporate bond would bepurchased regardless of where it is held as 5.1% (6%×(1-15%)) is greaterthan 4%.

An additional input for each bond is the taxable equivalent yield foreach municipal bond (or bond fund) and the tax-free equivalent yield foreach taxable bond. Alternatively the user simply inputs the general“spread” between taxable and tax-free bonds which the system applies toall bonds that are input. The system then optimizes the type of bond,calculating, based on a tax bracket input whether lower yieldingtax-free municipal bonds would be better for a particular investor. Insearching for the optimal location for the $10,000 in the bond exampleabove, the system would use 6% when trying retirement accounts and 4%tax-free for taxable accounts. These will obviously impact long-termaccumulation amounts and would also impact the optimal location ofbonds.

The output from the system would then be different for bonds. Otherinvestments will simply advise to keep the investment where it is or tosell all or part of it in its current location and purchase that amountin another account. A potential output with bonds for example might beto sell a corporate bond in a retirement account and then to buy adifferent but substantially equivalent investment—a municipal bond in ataxable account (or vice versa).

The system would typically shut down federal income taxes on municipalbonds. State taxability will be an additional input. Generally,municipals are taxable in the state of residence unless they are issuedby that state and Federal bonds may be tax-free at the state level. A“check the box” input for federal and state taxability would be used.

Another embodiment of the present invention uses multiple time horizons.For example, most people do not take their retirement accounts all outat once but rather spread out their withdrawals over a number of years.For example, they may wait until the IRS requires distributions at age70.5 and then withdraw based on IRS tables (i.e. ⅛th of account balanceeach year for the rest of their life). Alternatively, a ROTH IRA has norequired beginning date and as a result, may be the last investment aninvestor may draw down. In either case this keeps the tax deferredcompounding going for potentially many more years and as a result couldimpact which investments are best suited for the retirement accounts.Further, taxable accounts may also have different time horizons—forexample an investor may be setting money aside for a child's educationin 5 years. In a taxable account any appreciation on a stock is taxedwhen sold. Placing investments optimally is to a large extent dependenton the timing of taxation. Accordingly, if money from a collegeeducation account will be needed in 5 years it is wiser to put a buy andhold stock in another account that will not be needed for 30 years. Thiswould significantly delay the capital gains tax on its sale. The timevalue of money of paying taxes 25 years later would obviously enhanceoverall family net worth.

New inputs provide the anticipated date (or dates with amounts orpercentages of value) that each investment would be withdrawn. Theendpoint that defines optimization for example might be the maximumvalue at death, which are preprogrammed by life expectancy tables, asadjusted by the user. For families that may have an estate tax, then theaccumulation at death could be net of estate tax. Alternatively, forthose who might run out of funds prior to death, optimization aredefined as the maximum number of years that overall investments wouldlast. Note that the time horizons may be quite lengthy. Investments maybe passed to the next generation that may be named as beneficiary on aretirement account for example. Alternatively the investments may be ina trust for the benefit of a grandchild. Accordingly, there may be awide disparity in the time horizon of a family's investment accountsthat could have a material impact on the location of that family'sinvestments.

Another embodiment of the present invention provides for crossoverpoints. A user of the system might ask the question “how high a rate ofreturn is necessary to justify moving a given investment: from oneaccount to another?”. Often the highest total returning investmentshould be located in a retirement account but to move it from itstaxable account might involve paying current capital gains taxes as theinvestment in question has gone up in value. The system can trydifferent rates of return until it reached a different conclusion as towhere an investment should be located. The output will state “At a rateof return above 11% stock XYZ should be sold and repurchased in theretirement account, at a rate of 11% or below it should remain where itis”. The user can then make the decision whether or not to move XYZbased upon their judgement as to the likelihood of XYZ earning 11%. Thismay be much easier for the user than predicting a precise rate of returnon investments.

Similarly, there are other subjective inputs such as time horizon, aspreviously discussed. It may be difficult for the user to know how longthe investments may be held prior to withdrawal. For example, there canbe a tradeoff in some investments between paying tax along the way atfavorable rates in a taxable account or letting them grow in aretirement account without tax interference for many years and then betaxed at unfavorable rates (there are no capital gains rates availablein retirement accounts). Stocks may be a good example as the bulk oftheir return is from capital gains, which are taxed at a preferable rateof 20% when they are sold. Some investors may sell frequently and may bebetter off letting this higher potential earning investment grow in atax deferred environment where compounding may be significant. The morefrequent the sale and the further it is until retirement the moreattractive holding the stock in the retirement account may be. In thiscase the system will try different holding periods and different salefrequencies. The output will state “If the holding period is greaterthan 7 years move the investment to the retirement account, 7 years orless leave it in the taxable account” or “if the stocks are to be soldany more than every 3 years, they should be held in a retirementaccount”.

There are other subjective inputs that the system can calculatecrossover points for example, “How high could tax rates go up beforetaking advantage of low current capital gains rates by keeping stockinvestments in taxable accounts would be the better choice?”

Crossover points for more than one variable at a time is possible, butmore involved. The system goes through its normal optimization processwith Finite inputs. Then for the non-factual inputs, the system changesthem until the conclusion changed (there might also be a graphicalrepresentation of the crossover points). This is then reported to theuser who might then decide to change the input on that assumption. Thesystem then goes on to the next subjective input. This iterative processcontinues until the user was satisfied that the optimal solution wasachieved. For example—input 11% (best guess) for stock XYZ, system saysleave it where it is in the taxable account, system then indicatesthrough its crossover function that if return was greater than 11.8% itshould be sold and repurchased in the retirement account. The user maybe confident that the stock will earn at least 11.8% and will change theinput for this investment accordingly. This moves the investment intothe retirement account. Next the system address holding period forexample, etc.

Other optimization thresholds and variations are available, include anage 70½ (minimum required distributions), post-retirement investmentlocation optimization. Another optimization is crossover points for allthe variables that trigger when one account is better than another.Another optimization is differing time horizons for various accounts.Also, different beneficiary designations on retirement accounts can befactored in, i.e., Roth IRAs distributions could be delayed beyond theowner's death.

Other features of the present invention include input and output ofinformation in standardized formats, for example the Morningstar's orStandard and Poors etc. databases, allowing tie-ins for fund/individualsecurity data such as past returns, turnover, dividend yield, etc.Support for databases and/or spreadsheets of optimized portfolio as wellas current portfolio is helpful. Other support includes cash flowanalysis, with integration of projected cash flow needs to determinetime horizons for various investment accounts, and to integrate withexisting software programs that calculate retirement projections oroptimal investment mixes etc. Other features include a separateapplication which integrates into other standard systems, to extract thenecessary information and produce results with minimal data entry.

Other features include estate sensitivity, with no taxation onappreciation if assets passed via an estate; gifting, with implicationswithin family at different tax brackets, or to charity to escapetaxation on appreciation; tax basis, with current tax basis and relatedtax bite to be factored in when determining optimal account location;and tax-loss deductibility, to be factored in if securities decline invalue; different tax rates for different time periods; alternativeminimum tax if applicable. Obviously, as tax laws change, newoptimization features will become useful with the present invention. Thesoftware could also accommodate entirely different tax systems fromother countries, along with exchange rates as necessary.

Other features include a “solve it” function, for example to determinewhat minimum rate of return is needed before stock should be inretirement account or any other variable in the program; simultaneousoptimization of asset allocation with investment location; factoring inof ongoing cash inflows and outflows, a rebalancing feature, which tiesin anticipated rebalancing needs with current optimizations; and a taxefficiency calculator, to determine for example how much greater of aninvestment return does Fund A need to offset its tax inefficiency whencompared to Fund B.

The present invention also solves additional problem areas as follows:

Optimal Mortgage—Difficult decisions between fixed versus variable,points versus no points, 15-year versus 30-year, are all dependent on anumber of personalized assumptions—there are cross over points. OptimalAccount to Pay Investment Fees From—Investors Who pay advisory feesoften have many accounts which could be used to pay them. If paid fromtaxable accounts the fees may be deductible or perhaps partiallydeductible. If paid from retirement accounts the fees will reduce theeventual taxable distributions from those accounts at the price ofreduced long-term tax-deferred compounding. There are cross over points.Optimal Beneficiary Designations—Naming beneficiaries who are youngerthan your spouse can significantly increase long-term tax-deferredcompounding. However, your spouse may not have enough to live on shouldyou predecease them. Annuity Optimizer—Optimization is a function ofhigher cost of the annuity and loss of capital gains benefits versustax-deferred compounding through later required pay out dates and theability to annuitize. Optimal Time to Rebalance a Portfolio—The tradeoff between transaction costs and taxation versus increasedvolatility/risk and adherence to an investment policy can be optimized.Estate Planning—This is perhaps the most complex financial issue facingindividuals because there are such a wide range of possible objectivesand a wide range of means to achieve these objectives. This problemshares the basic characteristics of the investment location problem: itis bounded by the tax laws and is therefore optimizable. Optimizing TheUse of Stocks Versus Stockfunds—Factors include relative expenses,diversification issues, tax planning (i.e., harvesting losses), step-upin basis issues, charitable gifting, etc. Retirement Optimizer—Answeringthe reverse of the investment location question, this solution willanalyze an investor's portfolio and determine a schedule of optimaldistributions from tax-deferred and taxable investment accounts,factoring in liquidity needs, age 70½ minimum required distributionrules, tax basis, etc. Roth IRA Optimizer—Whether or not to convert anexisting IRA to a Roth is subject to a number of factors, some of whichare qualitative. Education Funding Optimizer—Optimizes a parent'sfunding alternatives between U-Plans, UTMA accounts, Educational IRAs,Educational Trusts, etc., factoring many issues including taxation,investment performance, financial aid, as well as qualitative factorssuch as control over investments. Stock Option Optimizer—Employees oftenown various types of stock options with a variety of restrictionsimpacted by tax laws and often subject to significant fluctuation invalue. The optimizer would present a schedule of which options tobuy/exercise/sell and when. Risk tolerance and stock volatility would befactored in. Life Insurance Optimizer—Whether to purchase term or cashvalue and if cash value, which type is a complicated issue which isoptimizable.

Although the invention has been shown and described with respect toillustrative embodiments thereof, various other changes, omissions andadditions in the form and detail thereof may be made therein withoutdeparting from the spirit and scope of the invention.

What is claimed is:
 1. A computer system for determining an investmentstrategy for an entity with assets in a taxable account, assets in atax-free account, and a mortgage, the system comprising interfacecomponents, a database, and an optimizer system, wherein the system isconfigured to: accept into the database information regarding: a totalasset amount, an amount of assets in a tax free account, an amount ofassets in a taxable account, a mortgage, a plurality of investments, anindicated percentage of the total assets to invest in each of theplurality of investments, and a time horizon; select, using theoptimizer system, amounts to invest from the taxable and tax-freeaccounts randomly or using Genetic Algorithms (GA), such that theamounts substantially match the indicated percentage of total assets toinvest in each of the plurality of investments; select, using theoptimizer system, a value for a mortgage variable; and calculate, usingthe optimizer system, a return on investment for the entity based on theselected amounts to invest, the selected value for the mortgagevariable, and the mortgage being paid out of the total asset amount;thereby determining an amount from the taxable and tax-free accounts toinvest in each of the plurality of investments and a value for themortgage variable that produce a maximal after-tax accumulation for saidentity at the time horizon.
 2. The computer system of claim 1 furtherconfigured to select values for three mortgage variables, wherein: thefirst value is one of fixed or variable; the second value is one ofpoints or no points; and the third value is one of 15-year or 30-year.3. The computer system of claim 1 further configured to: (a) select theamounts from the taxable and tax-free accounts randomly, and (b)calculate an after-tax accumulation for the entity based on the randomlyselected amounts.
 4. The system of claim 3 further configured to performsteps (a) and (b) a plurality of times, and output the selected amountsthat produce a maximal return.
 5. The system of claim 1 furtherconfigured to select amounts from the taxable and tax-free accountsusing Genetic Algorithms (GA) to produce a maximal return on investmentfor the entity at the time horizon.
 6. The system of claim 5 wherein theGA includes a chromosome structure, wherein the chromosome structureincludes a plurality of values, each value being an indication of anamount from the tax-free accounts to invest in a selected one of theplurality of investments, and wherein the system is further configuredto calculate an after-tax accumulation for the entity based on thevalues in the chromosome structure.
 7. A method of determining aninvestment strategy for assets of an entity, comprising: receiving intoa computer database in a computer system information regarding: aplurality of investments available in a taxable account as well as atax-free account; a total amount of available assets available toinvest; and, for each investment, a corresponding percentage of thetotal to be invested; receiving into the computer database informationregarding a time horizon and information regarding a mortgage includingat least one mortgage variable; defining within an optimizer system inthe computer system an effectiveness of an investment strategy as itscalculated yield at the time horizon after deducting a mortgage amount;where a chromosome is defined as a string of numbers comprising, foreach investment, an allocation of the corresponding percentage of thetotal between the taxable and the tax-free accounts and a value for themortgage variable, selecting, using the optimizer system, a samplechromosome and calculating a first effectiveness; selecting, using theoptimizer system, an additional chromosome and calculating a secondeffectiveness; for N generations, N>2: selecting, using the optimizersystem, an Nth chromosome; calculating, using the optimizer system, anNth effectiveness of the Nth chromosome; and choosing, using theoptimizer system, the investment strategy yielding the highesteffectiveness.
 8. The method of claim 7, wherein selecting the Nthchromosome comprises combining values from two previously selectedchromosomes to produce the Nth chromosome as one complete chromosome. 9.The method of claim 8, wherein the two previously selected chromosomesare chosen from among all previously selected chromosomes based on theircalculated effectiveness.
 10. The method of claim 7, wherein achromosome is further defined to include values for three mortgagevariables, wherein: the first value is one of fixed or variable; thesecond value is one of points or no points; and the third value is oneof 15-year or 30-year.
 11. The method of claim 7, further comprisingusing a Monte Carlo technique to select the sample chromosome or theadditional chromosome.
 12. A computer system for determining aninvestment strategy for an entity with assets in a taxable and atax-free account, the system comprising interface components, adatabase, and an optimizer system, wherein the system is configured to:accept into the database information regarding: a total asset amount, anamount of assets in the tax free account, an amount of assets in thetaxable account, a plurality of investments, an indicated percentage ofthe total assets to invest in each of the plurality of investments, atime horizon and an education time horizon; and select, using theoptimizer system, amounts to invest from the taxable and tax-freeaccounts randomly or using Genetic Algorithms (GA), such that theamounts substantially match the indicated percentage of total assets toinvest in each of the plurality of investments; such that thedeterminations will produce a substantially maximal after-taxaccumulation for the entity at the time horizon, after producing apre-determined accumulation for the entity at the education timehorizon.
 13. The system of claim 12, wherein the pre-determinedaccumulation for the entity at the education time horizon corresponds toa child's future cost of education.
 14. The system of claim 12, furtherconfigured to: accept into the database information regarding an amountof assets in an education account; and select, using the optimizersystem, amounts to invest from the education account randomly or usingGenetic Algorithms (GA), such that the determinations will produce asubstantially maximal after-tax accumulation for the entity at the timehorizon, after producing a pre-determined accumulation for the entity atthe education time horizon.
 15. The computer system of claim 14 furtherconfigured to: perform sampling steps a plurality of times, the samplingsteps comprising: randomly selecting amounts from the tax-free accountto invest in each of the plurality of investments; randomly selectingamounts from the education account to invest in each of the plurality ofinvestments; determining appropriate amounts from the taxable account sothat the selected percentage amounts for each of plurality ofinvestments is satisfied; and determining a result if the amounts wereinvested as selected and determined for the time horizon and theeducation time horizon.
 16. The computer system of claim 14 furtherconfigured to: create a plurality of GA chromosome structures, each GAchromosome structure including a value for each of the plurality ofinvestments, each value being an indication of an amount from thetax-free account to invest in the corresponding investment; set thevalues in the plurality of GA chromosome structures to initial settings;evaluate fitness of the plurality of GA chromosome structures; select atleast one of the GA chromosome structures with an optimal fitness; anduse the values from the selected GA chromosome structure as amounts fromthe tax-free account to invest in the corresponding investment for thesubstantially maximal accumulation.
 17. The computer system of claim 12further configured to calculate tax consequences over the time horizonand the education time horizon for the entity based on the selectedamounts to invest.